whisper-small-ha
This model is a fine-tuned version of openai/whisper-small on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7536
- Wer Ortho: 47.2867
- Wer: 44.1165
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.0713 | 3.18 | 500 | 0.6989 | 49.6836 | 46.2300 |
0.0145 | 6.37 | 1000 | 0.7536 | 47.2867 | 44.1165 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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